code: def _load_ts_data(config):
      task = config.task
      if config.is_multi_modal:
          train_data = MultiModalData.from_csv_time_series(
              file_path=config.input_data,
              task=task,
              target_column=config.target,
              columns_to_use=config.var_names,
          )
      else:
          train_data = InputData.from_csv_time_series(
              file_path=config.input_data,
              task=task,
              target_column=config.target,
          )
      return train_data
  
file_path: FEDOT/fedot/remote/run_pipeline.py
imports: import json
  import os
  import sys
  from typing import Union
  from golem.core.log import default_log
  from golem.utilities.random import RandomStateHandler
  from fedot.core.data.data import InputData
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.verification import verifier_for_task
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import TaskTypesEnum
  from fedot.remote.pipeline_run_config import PipelineRunConfig
label_desc: Use image node_id 2 for calling a global function with example usage: _load_ts_data(config) and returns: train_data